Novel nomogram for predicting acute kidney injury after cardiac surgery.

BACKGROUND: Acute kidney injury (AKI) is a common and serious complication after cardiac surgery, significantly impacting patient outcomes and healthcare systems. This study aimed to develop and validate a nomogram for predicting postoperative AKI in adults undergoing elective cardiac valve and coronary artery bypass graft surgery. METHODS: A clinical prediction study was conducted. The primary outcome was the occurrence of postoperative AKI. Potential predictors analyzed included demographic characteristics, comorbidities, preoperative laboratory values, anticoagulant medication usage, and intraoperative factors (transfusion volume, transfusion incidence, cardiopulmonary bypass duration, surgery type, perioperative bleeding). Multivariable logistic regression was used to identify independent predictors in a training cohort, and a nomogram was constructed. Model performance was assessed using the area under the receiver operating characteristic (ROC) curve (AUC) and validated in an independent cohort. RESULTS: Multivariable analysis identified older age [odds ratio (OR) =1.03; 95% confidence interval (CI): 1.02-1.04], preoperative hemoglobin (OR =0.98; 95% CI: 0.98-0.98), creatinine (OR =1.03; 95% CI: 1.02-1.03), higher intraoperative red blood cell transfusion volume (OR =1.07; 95% CI: 1.02-1.12), and increased perioperative bleeding (OR =1.00; 95% CI: 1.00-1.00) as independent predictors of AKI. This predictive nomogram demonstrated good discriminatory ability, with an AUC of 0.880 (95% CI: 0.867-0.894) in the training cohort and an AUC of 0.883 (95% CI: 0.863-0.904) in the internal validation cohort, and an AUC of 0.690 (95% CI: 0.671-0.709) in the external validation set. CONCLUSIONS: A nomogram incorporating five readily available clinical variables effectively predicts the risk of postoperative AKI in adults undergoing elective cardiac valve and bypass surgery. This tool may assist in preoperative risk stratification and guide perioperative management strategies.